Learn how easy it is to save and load scikit-learn models or pipelines. You can save a pipeline to disk. This is also a quick way to distribute new models to production.
- [Instructor] After we run some experiments,…and trained our model, normally the next step would be…to save it to disk and maybe ship it to production.…Again, sci-kit learn makes this easy.…In Python, we have a model called pickle,…which can store and retrieve almost any Python object.…The pickle format is Python specific…so we can't save a sci-kit learn model as pickle…and have Java load it.…With different production is using python as well,…this becomes a non-issue.…Let's try it out.…We'll import the pickle model…and then read open, model.pickle.…
And wb, writing in binary mode is out,…we do pickle.dump pipe, out.…Now we have a file called model.pickle.…We will directly use it, we will do with open model.pickle…and this time we read it in a binary format.…Let's call this one pipe1 =…pickle.load from the file.…And now we can use the model, let's do pipe1.steps…and these are the same steps we had before…and we can even do pipe1.score X test…and y test and get the same score as before.…
And the same way we save the model to a file,…
- Working with Jupyter notebooks
- Using code cells
- Extensions to the Python language
- Markdown cells
- Editing notebooks
- NumPy basics
- Broadcasting, array operations, and ufuncs
- Folium and Geo
- Machine learning with scikit-learn
- Plotting with matplotlib and bokeh
- Branching into Numba, Cython, deep learning, and NLP
Skill Level Intermediate
1. Scientific Python Overview
2. The Jupyter Notebook
3. NumPy Basics
Manage environments5m 11s
6. Folium and Geo
7. NY Taxi Data
10. Other Packages
11. Development Process
Next steps1m 33s
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